Terraform Foundations

Course Description

Terraform Foundations introduces Terraform from the perspective of a platform team creating repeatable infrastructure products. Learners begin with individual resources but quickly move toward conventions, reusable building blocks, and controlled team workflows.

The course emphasizes readable HCL, stable resource addressing, input contracts, state safety, module design, and plan review. Learners also use validation and lightweight tests to reduce infrastructure defects before apply.

The result is a foundational platform repository that can support multiple consumers without hiding operational risks or relying on one engineer’s local environment.

What You Will Learn

• Design and implement Infrastructure-as-code value and platform engineering context for Terraform Foundations.
• Validate HCL structure, providers, resources, and references, Dependency graph and plan reasoning, and Repository conventions, formatting, validation, and documentation through practical evidence and controlled change.
• Design and implement Variable types, validation, locals, and outputs for Terraform Foundations.
• Validate count versus for_each and stable keys, Maps, objects, collections, and conditional logic, and Sensitive values and consumer-facing contracts through practical evidence and controlled change.
• Design and implement State structure, resource addresses, and locking for Terraform Foundations.
• Validate Remote state and team collaboration, Drift, refresh, import, and moved resources, and Lifecycle, replacement, and destructive-change controls through practical evidence and controlled change.
• Design and implement Module interfaces, composition, and documentation for Terraform Foundations.
• Validate Versioning and backward-compatible module changes, terraform test, validation, linting, and security scanning concepts, and Release notes, examples, support, and consumer onboarding through practical evidence and controlled change.

SkillDynamo Training Approach

Learners create a small internal platform product in four iterations. Each iteration adds one professional practice—typed inputs, remote state, modules, or automated checks—so the final repository demonstrates progression from a script to a governed infrastructure product.